CPT: Pharmacometrics & Systems Pharmacology (May 2021)

Physiologically‐based pharmacokinetic modeling to support bioequivalence and approval of generic products: A case for diclofenac sodium topical gel, 1%

  • Eleftheria Tsakalozou,
  • Andrew Babiskin,
  • Liang Zhao

DOI
https://doi.org/10.1002/psp4.12600
Journal volume & issue
Vol. 10, no. 5
pp. 399 – 411

Abstract

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Abstract Establishing bioequivalence (BE) for dermatological drug products by conducting comparative clinical end point studies can be costly and the studies may not be sufficiently sensitive to detect certain formulation differences. Quantitative methods and modeling, such as physiologically‐based pharmacokinetic (PBPK) modeling, can support alternative BE approaches with reduced or no human testing. To enable PBPK modeling for regulatory decision making, models should be sufficiently verified and validated (V&V) for the intended purpose. This report illustrates the US Food and Drug Administration (FDA) approval of a generic diclofenac sodium topical gel that was based on a totality of evidence, including qualitative and quantitative sameness and physical and structural similarity to the reference product, an in vivo BE study with PK end points, and, more importantly, for the purposes of this report, a virtual BE assessment leveraging dermal PBPK modeling and simulation instead of a comparative clinical end point study in patients. The modeling approach characterized the relationship between systemic (plasma) and local (skin and synovial fluid) diclofenac exposure and demonstrated BE between the generic and reference products at the presumed site of action. Based on the fit‐for‐purpose modeling principle, the V&V process involved assessing observed data of diclofenac concentrations in skin tissues and plasma, and the overall performance of the modeling platform for relevant products. Using this case as an example, this report provides current scientific considerations on good practices for model V&V and the establishment of BE for dermatological drug products when leveraging PBPK modeling and simulation for regulatory decision making.